Company Intel

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description adds some behavioral context ('No login, no scraping, no proxies', pricing) but omits details on rate limits, authentication needs, or exact output structure beyond the listed signals.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that packs essential information. It is front-loaded with the main action, though it could be broken into two sentences for better readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain return values more thoroughly. It lists signals but lacks structure or detail on how results are organized, which is incomplete for a 4-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description mentions output signals (role count, functions, remote share) but does not elaborate on parameter usage beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('pull', 'turn into') and resources ('public job board', 'buying/expansion signal'). It clearly distinguishes from sibling tools like 'layoff-tracker' by focusing on open roles and hiring signals.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use as a buying/expansion signal, providing clear context. However, it does not explicitly state when to avoid this tool or recommend alternatives among the listed siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description covers important behaviors: it's a read-only lookup (no destructive actions), costs $0.01/call, requires no authentication, and returns a combined tech stack and registry match. It does not mention failure modes or rate limits, but these are minor gaps for a straightforward query tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise, conveying the main action and key details in a few sentences. It front-loads the core function. Some marketing language is present but does not detract significantly. Minor redundancy could be trimmed, but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains inputs and outputs at a high level, but without an output schema, the exact format of the 'company card' is unclear. The maxConcurrency parameter is explained. For an AI agent, this may be sufficient for selection but lacks structural detail about the response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the description adds value beyond the schema by explaining the pipe syntax for country hints, how LEIs are treated, and the purpose of maxConcurrency. This enhances the agent's understanding of parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: converting a domain or company name into a unified company card with website tech stack and GLEIF registry match. It specifies the inputs (domains, names, LEIs) and outputs, and is distinct from sibling tools which focus on specific aspects like hiring or funding.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context that the tool is keyless, no login, and built for AI agents and sales. It hints at when to use (company lookup) but does not explicitly compare to siblings or state when not to use. The caveat about country hints and LEI usage is helpful, but exclusion scenarios are missing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description bears full responsibility for behavioral disclosure. It discloses that the tool returns specific registry fields, optionally enriches with UK directors/SIC codes, costs $0.01 per call, and uses blockchain payment (x402 USDC on base). No destructive behavior or rate limits are mentioned, but the information is relevant and non-contradictory.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—one sentence plus a cost note. It front-loads the core purpose and includes only essential details. Every phrase adds value, with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description clearly specifies the return fields (legal name, status, jurisdiction, registered address, LEI, and optionally directors/SIC codes). It also covers input variants, optionality, cost, and the payment method, making it complete for an agent to understand the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have 100% schema description coverage. The description adds significant value beyond the schema by explaining the pipe syntax for country hints, how LEIs/UK numbers bypass name search, and the purpose of the optional API key. This extra context is highly beneficial for correct parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'turn into' and the resource 'official registry card', listing specific fields (legal name, status, jurisdiction, registered address, LEI). It distinguishes from sibling tools like 'company-lookup' by specifying enrichment functionality via GLEIF and optional UK data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool (turning company names, LEIs, or UK numbers into registry cards) and explains optional enrichment with a Companies House API key. It does not explicitly state when not to use it or list alternative tools, but the purpose is sufficiently defined.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses pricing ($0.08/call), USDC payment, and partial card behavior. No destructive behavior indicated; description aligns with expected read-only operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with front-loaded purpose and essential cost info. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description should clarify return format. Mentions 'one card' and 'partial cards' but omits which signals are rolled up. Leaves some ambiguity about output details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all 4 parameters with descriptions. The description adds no new parameter-level details beyond what the schema already provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it summarizes changes per competitor over a week, using a specific verb and resource. However, it does not explicitly differentiate from sibling rollup tools like counterparty-risk-rollup, leaving the distinct signals vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies use for weekly competitor change summaries, and mentions partial card handling. But no explicit guidance on when not to use or direct alternatives among the 18 sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully covers behavioral traits: it discloses data sources, output format (one row per company with risk score), cost ($0.03/call), concurrency handling, jurisdiction hint normalization, and relative speed of checks. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first clearly states the tool's purpose and scope, the second adds pricing and technology details. Every word earns its place, no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains the output format (one row per company with risk score) but does not detail how the risk score is computed or error handling. For a tool with four parameters and consolidated output, it is largely complete, though a bit more on the risk score would help.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions. The description adds significant value beyond the schema by explaining the meaning of each check, the speed implications, jurisdiction hint synonym handling, and concurrency meaning. This elevates it above the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool screens a counterparty by combining multiple checks (sanctions, registry, litigation, hiring) into one row per company with a risk score. It uses specific verbs and resources and distinguishes itself from sibling tools like sanctions-screening and litigation-check by being a consolidated rollup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (for a consolidated risk assessment) and provides context on speed, pricing, and optional parameters. However, it does not explicitly state when not to use it or name specific alternatives, leaving that implicit from sibling tool names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

In the absence of annotations, the description discloses key behavioral traits: it checks syntax, domain, and MX records, and returns null instead of guessing when mailbox existence cannot be established. It also mentions pricing. However, it does not cover rate limits or authentication.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences plus a cost note. It front-loads the main functionality and avoids unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description explains the null behavior for undeterminable mailbox existence, which compensates for the lack of an output schema. It does not detail the full response structure or error handling, but is largely complete for a simple verification tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds context about the tool's checks but does not enhance parameter semantics beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it checks email addresses for syntax, domain, and mail exchangers, which is a specific verb+resource combination. It also distinguishes from siblings by specifying its functionality, as no other sibling tool focuses on email verification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for email verification but does not explicitly state when to use this tool versus alternatives. No when-not or exclusion criteria are provided, though the cost mention hints at paid usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions delta behavior and first-run baseline, but does not disclose whether the tool is read-only or has side effects (e.g., storing state), which is critical given its stateful nature. Cost and 'x402 (USDC on base)' are unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise: two sentences plus cost note. No redundant information. However, the cost line could be more machine-readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations. Description does not specify output format or fields, leaving agents to guess. The underlying filing type (SEC Form D) is only in param descriptions, not highlighted. Given tool complexity with 5 params, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with good parameter descriptions. The overall description adds context about delta behavior and first-run, but doesn't add significant meaning beyond the schema for individual parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool watches saved filters for funding announcements and returns only changes from previous check. Verb 'watches' and 'returns' with resource 'funding announcements' are specific. However, no differentiation from sibling 'funding-round-tracker'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use or not use this tool versus alternatives like 'funding-round-tracker'. Usage is implied for ongoing monitoring, but no exclusions or conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description provides good behavioral context: it is a free, official SEC EDGAR search, no API key needed, and lists the output fields (company, filing date, document URL). It also mentions cost. However, it could be more thorough about rate limits or pagination.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the main purpose, and each sentence adds value. No wasted words. It is efficiently structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains what is returned (company, filing date, document URL). It covers the key output fields. However, it could mention handling of empty results or pagination. Overall, fairly complete for a simple tracker.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all four parameters. The description adds no additional parameter semantics beyond what is in the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks SEC Form D filings by company name or sector keyword. It specifies the resource (SEC Form D), the verb (track), and the scope (by company or sector). This distinguishes it from sibling tools like layoff-tracker or patent-monitor.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the tool is for tracking SEC Form D filings, is free and requires no login. While it doesn't explicitly state alternatives or when not to use, the tool is unique among siblings, so the context is clear. A score of 4 is appropriate as it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that results may be partial and lists what is missing. It also mentions cost, but does not cover rate limits, authentication, or other behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences and is front-loaded with the core purpose. It is concise yet informative, though the inclusion of cost could be considered extraneous.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the three parameters are well-documented in the schema and the description covers partial results and missing data, the tool definition is nearly complete. No output schema exists, but the description addresses return value context adequately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter has a schema description. The tool description adds extra context for the 'slices' parameter by explaining the two forms and their behavior, but this is moderate added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides a cross-section of hiring demand by role and geography from multiple job sources in one call. This verb+resource combination is specific and distinguishes it from the sibling tool company-hiring-radar, which focuses on a single company.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains how to interpret partial results and mentions cost, giving clear usage context. It does not explicitly state when not to use this tool vs. alternatives, but the aggregate nature is implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool uses public data and combines signals, but does not reveal the score range, data freshness, update frequency, or any limitations. The cost is mentioned but not tied to rate limits or throttling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences that front-load the core question, followed by a succinct explanation of functionality and key benefits. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the tool's complexity (aggregating multiple data sources into a score), there is no output schema and the description does not explain what the returned intent score looks like (format, scale, or additional fields). This omission leaves the agent without crucial context for handling responses.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description text adds no further detail beyond what the schema already provides for the parameters; it does not explain the format or options for 'companies' beyond the schema's own description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear question ('Is this company in-market right now?') and explicitly states that it combines hiring activity and news into one intent score per company. This distinguishes it from sibling tools that focus on individual signals like hiring radar or funding trackers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions ease of use (no login/API keys/proxies) and cost, implying it's for quick checks, but does not explicitly state when to use this aggregator versus the more specialized sibling tools (e.g., company-hiring-radar, funding-round-tracker). Guidance on when-not-to-use is absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full transparency burden. It explicitly states 'No login, no scraping, no proxies,' indicating read-only operation and no setup. It also discloses the cost ($0.01/call) and payment method (USDC on base). However, it does not mention latency, failure modes, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that starts with the core action, followed by key behavioral traits and outputs. It is concise but includes pricing information which, while relevant, slightly detracts from focus. Generally well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with 3 parameters and no output schema, the description covers input format, search logic, source, outputs (headlines, count, summary), and cost. It could be more specific about the output format, but overall it provides sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds value for the 'queries' parameter by explaining it searches '{query} layoffs' in Google News and providing examples. For 'sinceDays' and 'maxConcurrency', the description does not add beyond schema defaults, but the overall semantic enhancement merits a score above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the tool's purpose: tracking recent tech layoffs by company or sector from Google News. It uses a specific verb ('track') and resource ('layoffs'), effectively differentiating it from sibling tools like 'company-hiring-radar' which focus on hiring.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description positions the tool as a 'demand and recruiting signal,' implying usage for monitoring layoffs. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'company-hiring-radar') and does not mention appropriate or inappropriate contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses pricing ($0.05/call), the identity confidence heuristic ('guessed when no override'), and a run cap (25 per run). However, it omits details about output format, error handling, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loads the core purpose, and includes essential behavioral notes (pricing, identity treatment). No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain what the tool returns (e.g., score format, fields). It mentions 'scores' and 'Identity confidence' but not other output details. The description is adequate for a simple tool but leaves gaps for full understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds some context (e.g., pricing, identity honesty) but does not significantly enhance the parameter explanations beyond the schema. There is a minor inconsistency: schema maxItems=10 but description says capped at 25.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scores domains for buying readiness using multiple signal sources, which is a specific verb+resource. It distinguishes this aggregator from the individual signal tools listed as siblings (e.g., company-hiring-radar, funding-round-tracker) by emphasizing the combined call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool over alternatives. It does not mention prerequisites, when to avoid it, or compare to sibling tools. The only usage hint is in the parameter descriptions (e.g., role_keywords is optional).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses keyless access, one-row-per-jurisdiction output, true case counts, cost ($0.03/call), budget limits with early termination behavior, and limitations (e.g., PL keyword mention, approximate counts for large matches). This is comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense paragraph that efficiently conveys core purpose, cost, and behavior. While not perfectly structured, it wastes no words and front-loads the key action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains output format (one row per company x jurisdiction, case count, links), edge cases (budget exhaustion, unsupported jurisdictions), and references a README for further details. It is complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds minimal extra per-parameter detail beyond what the schema already provides, though it does integrate context (e.g., budget, jurisdiction behavior) that isn't in schema fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool screens companies for litigation history across US, UK, and Polish jurisdictions. It specifies the data sources (CourtListener, UK case law, Polish SAOS) and differentiates from sibling tools that focus on hiring, registry, patents, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for litigation checks and notes jurisdiction-specific nuances (PL is keyword mention, unsupported jurisdiction returns graceful row). It does not explicitly state when to use vs. alternatives, but no other sibling tool covers litigation history, so context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears the full burden. It discloses the data source, default window, and that no API key is needed, but omits details like rate limits, pagination, or result sorting. For a tool with no annotations, this is adequate but has gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Exceptionally concise: two sentences plus a pricing note. Front-loads the core purpose and key constraints. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity and full schema coverage, the description is mostly complete. It explains the data source, default behavior, and cost. However, it lacks description of the output format (e.g., what fields are returned), which would help the agent anticipate results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema descriptions; it merely restates the default window. Since the schema already fully documents all parameters, no additional value is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool finds newly-incorporated UK companies matching a keyword, specifying data source (Companies House) and default window. However, it does not explicitly differentiate from sibling tools like company-hiring-radar or company-lookup, which could cause ambiguity for the agent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage for finding new UK companies and mentions ease of use (no API key), but provides no guidance on when not to use this tool or alternative tools from the sibling list. The agent must infer context from the tool name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the external API dependency (PatentsView or Google Patents), cost ($0.02/call), and data freshness (sorted by most recent). It omits error handling or rate limits, but the core read-only behavior is well described.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (3 sentences) and front-loaded with the main purpose. It efficiently covers all key aspects without redundancy. Minor cost and API details are appropriately placed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (5 parameters, no output schema), the description adequately explains inputs and output shape. It mentions return fields and sorting, but lacks details on pagination or error cases, which would be helpful for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, providing baseline 3. The description adds value by explaining the dual behavior of the API key (keyless Google source vs USPTO-backed PatentsView) and clarifying the purpose of parameters like queries and sinceDays in the context of patent monitoring.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: monitoring keywords for newly granted US patents. It specifies the returned fields (patent id, title, grant date, assignee, Google Patents link) and sorting order, making it unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains when to use the tool (to watch patents) and mentions alternative data sources (PatentsView vs Google Patents). It does not explicitly contrast with sibling tools, but the sibling tools are for different domains (companies, funding), so the usage context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the burden. It clearly states the tool is free and lists information (non-destructive trait). No mention of side effects or rate limits, but sufficient for a simple read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence conveying purpose and usage guideline with no filler. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters, no output schema, and simple listing task, the description adequately covers what the tool does and when to use it. Could optionally hint at output format, but not necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters yields a baseline of 4. The description does not need to add param info since none exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('list'), resource ('every paid tool in the 'company-intel' bundle'), and scope ('with its price, payTo address and network'). It distinguishes this tool from siblings that cover other company intelligence aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises calling this tool first if the user doesn't have a wallet ready, providing clear when-to-use context that differentiates it from sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses key behavioral traits: 'Keyless, no login,' 'live' data, 'flags potential hits with a match score,' and the scoring is 'soft' to avoid missed hits. However, it does not cover rate limits, error behavior, or output structure beyond 'potential hits.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences plus a pricing tagline. Every sentence adds value: the first states core function and lists, the second adds use case and key features (keyless, login-free, match score). The pricing is a bonus. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (3 params, no output schema), so completeness is moderate. It lacks an explicit description of the output format (e.g., list of matches with scores, names, details). While the purpose is clear and parameters are well-explained, the absence of output details leaves a gap for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaningful context beyond the schema: explains 'names' as one per row, minScore's soft heuristic ('a missed hit is worse than a false one'), and maxConcurrency as parallelism. This enhances understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Screen names against the live OFAC SDN and EU consolidated sanctions lists.' The verb 'screen' and specific list references make it unambiguous, and it distinguishes itself from siblings (none are similar).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context: 'so you can review before onboarding a client or counterparty,' indicating when to use it. However, it does not explicitly state when not to use it or suggest alternatives, but no comparable siblings exist, so the guidance is adequate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the first run creates a baseline, that only status-changed entries are returned, and includes pricing. It does not cover rate limits or idempotency, but the key behaviors are addressed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences plus pricing, conveying essential information without filler. It is front-loaded with the core function and efficiently structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 parameters (well-described in schema) and no output schema. The description explains the update-alert nature and the first-run behavior, but does not describe the output format or clarify how the baseline is stored. Still, it covers the major contextual points.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The tool description itself adds no additional parameter-level meaning beyond the already detailed schema descriptions. No deduction or bonus needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it re-screens a saved watchlist and returns only changed entries, distinguishing it from a full initial screening. The specific verb 're-screens' and the mention of baseline creation make the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly indicates use for ongoing monitoring vs. one-off screening, but does not explicitly name siblings or provide when-not-to-use guidance. The context is clear enough for an agent to infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key behaviors: it visits fixed pages, extracts contacts, flags third-party/placeholder addresses, and mentions pricing. No side effects or destructive actions are implied, and no contradictions with annotations (since none provided).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is two sentences, front-loading the core purpose and key feature. The pricing info could be moved to a separate section but does not severely impact conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description and schema cover parameter behavior well but omit output format details (no output schema). The honesty check feature adds context, but return value structure is missing, leaving some ambiguity for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions. The tool description does not add significant meaning beyond the schema beyond mentioning the honesty check and pricing, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb (extract), resource (public contacts from a company's own site), and specific outputs (email, phone, social links). The honesty check feature distinguishes it from sibling tools like email-verifier or generic scrapers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use or not use this tool vs alternatives like email-verifier. The description implies the honesty check is valuable but does not state prerequisites or exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.